1. Field of the Invention
The present invention relates to a digital image processing system and, more particularly, to a data compression system employing a coding system of grey level text image data, in consideration of text images and combined resultant images.
2. Background Description
According to the background art, in order to form grey level text images such as character images in a word processor, the grey level character images are formed by the method of quantization in which the quantization level is determined arbitrarily, as in other digital image formation.
Generally, a grey level image is formed by a plurality of pixels aligned in two orthogonal directions, each pixel having a white, black or intermediate gray valve, expressed by n bits of data. For example, white is expressed by all ones (111 . . . 1); black is expressed by all zeros (000 . . . 0); and intermediate gray is expressed by a combination of ones and zeros In FIG. 1, an example of a 4.times.5 pixel image is shown in which the first pixel from the left in the first row is white (11 . . . 1). The second pixel in the first row is gray (11 . . . 0), the third pixel is black (00 . . . 0), and the fourth pixel is gray (10 . . . 1). Such an image formed by binary data with each pixel expressed by N bits is generally referred to as an N-bit plane image.
When the data for the grey level text image is to be compressed by the coding method, a bit plane dividing method is first effected to pretreat the image data to produce a series of binary data. Then, a data compression method, such as run length coding is effected.
The bit plane dividing method is diagrammatically shown in FIG. 1. Since each pixel contains N bits, N sheets of bit planes are prepared and are numbered from first to Nth. The Nth bit plane is defined by the collection of the most significant bit from each pixel, and the collected bits are aligned at corresponding pixel positions in the Nth bit plane. Similarly, the (N-1)th bit plane is defined by the collection of the second most significant bit from each pixel, and so on. The first bit plane is defined by the collection of the least significant bit from each pixel.
To store the image data, first, the binary data on the Nth bit plane are serially read out from the top row to the bottom row, and then the data on the (N-1)th bit plane are serially read out, and so on, until the first bit plane, and the readout data are serially stored in a suitable storing means. According to this method, in total, 4.times.5.times.N bits will be stored in the storing means.
To compress the data to be stored, run length coding, e.g., modified Huffman coding or modified read coding (a kind of two dimensional coding), is used. For example, if the run length coding is used, a long run of "1" or "0" data can be compressed such that, instead of repeating the same data "1" or "0", a code indicating the data length and a code indicating the type of repeated data is inserted.
The conventional compression coding system as described above is formed in the light of the fact that the data representing the background area, usually white area, occupies a great percentage of the total data. However, with grey level text image, the dynamic range of the intensity level (between white and black) may not be fully utilized, as shown in FIGS. 2a and 2b, in which FIG. 2a shows a case wherein the dynamic range width is not fully utilized, and FIG. 2b shows a case wherein the dynamic range is shifted. Thus, in the prior art compression coding system, since the distribution pattern differs with respect to different original images, the compression coding can not be carried out with the use of a fixed quantization level, as further explained below with an example of a P-level text image.
The P-level text image includes pixels representing white background portions, black text image portions depicted on the white background, and boundary portions between the background portion and black text image portion. Quantization is effected such that the white background portions are assigned with a maximum level (P-1), the black text image portions are assigned with a minimum level (0), and the boundary portions are assigned with intermediate levels (1 through P-2). Statistically, the pixels with the maximum level (P-1), representing the white area, occupy the greatest percentage, such as greater than 90%. The next greatest percentage would be about several percent occupied by the pixels with the minimum level (0), representing the black area. The remaining pixels, with the intermediate levels (1 through P-2) for the boundary areas (edge portions), typically occupy a very small percentage. The percentages given in the above example are based on a 3-bit image including 512.times.512 pixels.
According to the conventional coding system employing the bit plane dividing method described above, the bit planes carrying binary images have strong correlation. For example, in the case of an N-bit image, the binary data at the pixel position representing white would be "1" for all the bit planes. Thus, the bit images on the bit planes would be very similar to each other. When each bit plane is coded, the same or a similar coded pattern would be repeated, resulting in high redundancy. Thus, according to the prior art coding system, since similar binary images on a plurality of bit planes (i.e., with strong correlation) are coded, the data compression can not be carried out with a high compression rate.